An Exploration of Provincial Low-Carbon Economy Evaluation System Based on Principal Component-Variable Fuzzy Evaluation

Abstract

According to indicators’ information repetition and subjectivity of the indicators’ weight set during the variable fuzzy comprehensive evaluation, Principal Component analysis can help solve the weight of the relative indicators and reduce comprehensive evaluation dimensions of the variable fussy comprehensive evaluation. This paper has made a comprehensive evaluation of the status quo of Yunnan’s low carbon economy development(2005-2009), which turns out to be more practical compared with the mere variable fussy theory analysis, thus, principal component-variable fuzzy evaluation is a kind of feasible way to analyze the regional low carbon development status.

Environmental Performance Evaluation of New Type Thermal Power Enterprises Considering Carbon Peak and Neutrality

“…It can monitor the operation and benefits of the system in a timely manner and output quantitative evaluation results, which is helpful for enterprises to apply improvement measures for bad results and bad indicators. At present, academia uses the Delphi method [24,25], analytic hierarchy process [26], fuzzy comprehensive evaluation model [27], factor analysis [28], principal component analysis [29], multi-objective decision-making [30], data envelopment analysis [31], and other models to evaluate environmental performance.…”